Some digitized processing techniques developed for remote infrared vapor signal detecting, such as pattern classification, frequency－domain digital filtering and time－domain digital filtering, are introduced. The applications of linear discriminant, piecewise linear discriminant and artificial neural network on remote infrared chemical sensing are preliminarily discussed. The background subtraction, frequency－domain digital filtering and the apodization methods for digital filtering are briefly described. The principle and the usage of time－domain filtering are illustrated. An outlook on digitized signal processing algorithms for remote infrared chemical sensing is given.